Multicommodity information flow through quantum annealer

Quantum computing offers a novel perspective for solving classically intractable problems. The computational heuristic non-binary nature of quantum computers, based on quantum mechanical properties, associates several advantages and disadvantages. We explore quantum annealing (QA), a metaheuristic algorithm with the primary objective of solving NP-hard optimization problems intractable to classical algorithms. Here we solve a particular family of NP problems, called origin–destination integer multi-commodity flow problem (ODIMCF), using QA. This includes the quadratic unconstrained binary optimization (QUBO) formulation and the practical implementation of this problem on the D-Wave QA. Additionally, quantum annealers are benchmarked against other classical solvers to assess the ODIMCF problem’s solution quality and runtime performance.